Rainbow boxes: A new technique for overlapping set visualization and two applications in the biomedical domain

• Published in: Journal of visual languages and computing Vol. 43; pp. 71 - 82
• Main Authors: Lamy, Jean-Baptiste, Berthelot, Hélène, Capron, Coralie, Favre, Madeleine
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2017; Elsevier; Academic Press
• Subjects: Artificial Intelligence; Computer Science; Computer Science Applications; Drug properties; Gene annotation; Graphics; Human-Computer Interaction; Information visualization; Knowledge visualization; Language and Linguistics; Life Sciences; Overlapping set visualization; Santé publique et épidémiologie; Sciences du vivant; User study; Overlapping set visualization; Drug properties; Information visualization; Knowledge visualization; Gene annotation; User study
• ISSN: 1045-926X; 1095-8533; 1095-8533
• DOI: 10.1016/j.jvlc.2017.09.003

•Rainbow boxes are a new technique for overlapping set visualization.•They help discover similarities in rather small datasets.•A first application is the comparison of drug properties.•A second application is the visualization of gene annotation. Overlapping set visualization is a well-known problem in information visualization. This problem considers elements and sets containing all or part of the elements, a given element possibly belonging to more than one set. A typical example is the properties of the 20 amino-acids. A more complex application is the visual comparison of the contraindications or the adverse effects of several similar drugs. The knowledge involved is voluminous, each drug has many contraindications and adverse effects, some of them are shared with other drugs. Another real-life application is the visualization of gene annotation, each gene product being annotated with several annotation terms indicating the associated biological processes, molecular functions and cellular components. In this paper, we present rainbow boxes, a novel technique for visualizing overlapping sets, and its application to the presentation of the properties of amino-acids, the comparison of drug properties, and the visualization of gene annotation. This technique requires solving a combinatorial optimization problem; we propose a specific heuristic and we evaluate and compare it to general optimization algorithms. We also describe a user study comparing rainbow boxes to tables and showing that the former allowed physicians to find information significantly faster. Finally, we discuss the limits and the perspectives of rainbow boxes.